Arctic cyanobacterial mat community diversity decreases with latitude across the Canadian Arctic

Abstract Cyanobacterial mats are commonly reported as hotspots of microbial diversity across polar environments. These thick, multilayered microbial communities provide a refuge from extreme environmental conditions, with many species able to grow and coexist despite the low allochthonous nutrient inputs. The visibly dominant phototrophic biomass is dependent on internal nutrient recycling by heterotrophic organisms within the mats; however, the specific contribution of heterotrophic protists remains little explored. In this study, mat community diversity was examined along a latitudinal gradient (55–83°N), spanning subarctic taiga, tundra, polar desert, and the High Arctic ice shelves. The prokaryotic and eukaryotic communities were targeted, respectively, by V4 16S ribosomal RNA (rRNA) and V9 18S rRNA gene amplicon high-throughput sequencing. Prokaryotic and eukaryotic richness decreased, in tandem with decreasing temperatures and shorter seasons of light availability, from the subarctic to the High Arctic. Taxonomy-based annotation of the protist community revealed diverse phototrophic, mixotrophic, and heterotrophic genera in all mat communities, with fewer parasitic taxa in High Arctic communities. Co-occurrence network analysis identified greater heterogeneity in eukaryotic than prokaryotic community structure among cyanobacterial mats across the Canadian Arctic. Our findings highlight the sensitivity of microbial eukaryotes to environmental gradients across northern high latitudes.


Introduction
The Arctic is warming consider abl y faster than the global av er a ge, altering aquatic environments and the biodiversity within (Rantanen et al. 2022 ).Micr obial mats dominated by phototr ophic oscillatorian c y anobacteria, her eafter r eferr ed to as c y anobacterial mats, are a common feature of aquatic ecosystems in the polar regions (Vincent et al. 2000, Jungblut et al. 2010 ).Cyanobacterial mats are often the major drivers of organic carbon fixation and nutrient cycling in Arctic aquatic ecosystems (Vincent et al. 2000, Varin et al. 2010 ).The m ultilayer ed thr ee-dimensional structur e of c y anobacterial mats cr eates a micr ohabitat for div erse micr obial comm unities, pr oviding r efuge fr om the str esses imposed by polar en vironments , including persistent low temper atur es, low allochthonous nutrient input, and repeated extreme annual light and freeze-thaw cycles (Vincent et al. 2000, Jungblut et al. 2012, Velázquez et al. 2017 ).Internal nutrient recycling and scavenging by heter otr ophic bacteria, fungi, and viruses in the c y anobacterial mat communities creates a nutrient-rich environment within often oligotrophic Arctic aquatic ecosystems (Varin et al. 2010, Vigneron et al. 2018 ).
Eukaryotic microbes and microfauna have been observed in polar microbial mat communities since the earliest microscopic investigation of Antarctic mats (Murray 1910 ).More recently, 18S ribosomal RNA (18S rRNA) gene clone library surveys (Jungblut et al. 2012 ) and metagenomic (Varin et al. 2010, Vigneron et al. 2018 ) sequencing of microbial mat communities in the Canadian High Arctic identified algae and heter otr ophic pr otists, microfauna, and fungi.Almela et al. ( 2019 ) demonstrated using DNA sequencing and stable isotope assays that multiple trophic le v els ar e pr esent within Antarctic micr obial mat comm unities, where carbon is transferred from primary production by c y anobacteria and diatoms to metazoan consumers, including rotifers , tardigrades , and nematodes , and rec ycled b y fungal decomposers.Ho w e v er, their a ppr oac h did not consider heter otr ophic pr otists.Heter otr ophic pr otists exhibit div erse ecological functions , including bacterivores , eukaryvores , mixotrophs , parasites , and pathogens, meaning that protists commonly occupy multiple tr ophic le v els in envir onmental micr obiomes (Arndt and Nomdedeu 2016 ).Mor eov er, pr otist gr azers contribute to nutrient cycling in temperate stream biofilm communities (Battin et al. 2016 ).
A compr ehensiv e anal ysis of the eukaryotic community is therefor e r equir ed to obtain a mor e complete understanding of the potential trophic interactions and contribution to nutrient recycling by microbial eukaryotes within polar cyanobacterial mat communities (Jungblut et al. 2012 ).
The Canadian North spans distinct ecozones across a continuous gradient of environmental severity from the subarctic boreal taiga, through the open tundra, to the polar desert and ice shelves of the High Arctic, eac h c har acterized by distinct vegetation and climatic regimes, but all consistently rich in aquatic ecosystems (Vincent andLaybourn-Parry 2008 , Wrona et al. 2016 ).Streams, rivers, and meltwater ponds are consistent across the Arctic region, while per enniall y ice-cov er ed lakes and ice shelf meltwater ponds are specific to the High Arctic, due to the extended periods of below freezing temperatures (Vincent et al. 2000, Jungblut et al. 2017 ).While the habitat c har acteristics of Arctic aquatic ecosystems vary broadly, they all commonly host benthic c y anobacterial mat communities (Jungblut et al. 2010 ).Accor dingly, c y anobacterial mats are useful as compar ativ e micr obial comm unities for div erse biogeogr a phical questions and for elucidating the influence of abiotic drivers, including potential climate-driven environmental change, on microbial diversity.
To date, most studies on c y anobacterial mats in the Arctic r egion hav e been r estricted to a fe w specific habitats or hav e been limited to either prokaryotes or microbial eukaryotes (de los Ríos et al. 2004, Varin et al. 2012, Jungblut et al. 2017 ).In this study, we e v aluated the pr okary otic and eukary otic diversity in c y anobacterial mats in terrestrial aquatic environments of the Canadian North, across a broad latitudinal gradient from the subarctic taiga to the High Arctic ice shelves (55-83 • N), using 16S rRNA and 18S rRNA gene amplicon high-throughput sequencing.We hypothesized that prokaryotic and eukaryotic diversity within c y anobacterial mat communities would decrease with increasing latitude across the Canadian Arctic, in response to gradients of less favourable climatic conditions for net growth, similar to terrestrial fauna and flora (Wrona et al. 2016 ).The influence of envir onmental v ariables on comm unity ric hness and e v enness was assessed.The functional contribution of the pr otist comm unity was further assessed following taxonomy-based assignment into br oad tr ophic functions (Adl et al. 2019, Singer et al. 2021 ).Finall y, co-occurr ence networks wer e cr eated to identify interactions within and between the prokaryotic and eukaryotic communities, within the c y anobacterial mats.

Sample collection and environmental conditions
Cy anobacterial mats w er e collected fr om terr estrial aquatic envir onments acr oss the Canadian North.Benthic mat samples from lakes and ponds were collected near the hamlets of Kuujjuarapik, Umiujaq, Cambridge Bay, and Resolute, and from Bylot Island, Ward Hunt Lake on Ward Hunt Island, and Antoniades Pond on Ellesmere Island.Less terrestrially influenced mats were collected from ice-based surface meltwater ponds from the Markham Ice Shelf and Ward Hunt Ice Shelf ( Supplementary Fig. S1 ; Table 1 ).Mat samples were collected in triplicate, except for Bylot Island and Resolute sites due to sampling time constraints.Samples were collected at water depths of 10-20 cm using a sterilized steel spatula and tr ansferr ed to a sterile Falcon™ 50-ml centrifuge tube.Samples wer e stor ed at −20 • C in field laboratories before being transported to the Natural History Museum, London, UK, for stor a ge at −80 • C until DNA extraction.At each sample site, GPS coor dinates, w ater specific conductivity ( μS cm −1 ), pH, and temper atur e wer e measur ed at the sampling depth using a pH/Con 10 series probe (Oakton Instruments, UK).Average monthly air temper atur e data were extracted from Nordicana D (CEN 2020(CEN , 2021(CEN , 2022a ,b ) ,b ) and the Environment and Climate Change Canada Historical Climate Data (McKenney et al. 2011, MacDonald et al. 2020 ) arc hiv es.

DN A extr action, pol ymer ase chain reaction, and amplicon sequencing
DN A w as extr acted fr om c y anobacterial mat samples using the Po w erBiofilm™ DN A Extraction Kit (MO BIO Laboratories, Carlsbad, CA, USA), following the manufacturer's guidelines.In the absence of triplicate samples, triplicate DN A extractions w ere carried out on portions of the same mat sample from Resolute and Bylot Island.Extracted DN A w as amplified b y pol ymer ase c hain reaction (PCR).For 16S rRNA gene sequencing, 260 bp of the V4 region of the prokary otic 16S rRN A gene w as amplified using the 515f-806r primers (Ca por aso et al. 2012 ).For 18S rRNA gene sequencing, 130 bp of the V9 region of the eukaryotic 18S rRNA gene was amplified using 1391f-EukBr primers (Amaral-Zettler et al. 2009 ).For each sample, triplicate PCR samples were amplified with 0.5, 1, and 1.5 μl volumes of template DNA, to accommodate potential amplification bias.For sequencing, the primers were composed of an Illumina adaptor, unique Golay barcode (reverse primers only), primer pad, and primer linker sequences.PCRs were carried out in 20 μl reaction volumes consisting of 4 μl 5x GoTaq reaction buffer (Promega, Madison, WI, USA), 2 μl MgCl (25 mM), 0.8 μl bovine serum albumin (20 mg ml −1 ), 0.16 μl dNTPs (25 mM), 1 μl forw ar d primer (10 μM), 1 μl r e v erse primer (10 μM), 9.84 μl PCR-grade deionized H 2 O, and 0.2 μl GoTaq ® DNA polymer ase (Pr omega, Madison, WI, USA).The thermocycling conditions consisted of an initial denaturation at 94 • C for 4 min, follo w ed b y 35 c ycles of denaturation at 94 • C for 30 s, annealing at 50 • C for 30 s, extension at 72 • C for 2 min, and a final extension at 72 • C for 7 min.PCR pr oducts wer e visualized by gel electr ophor esis, run on a 1% a gar ose gel for 35 min at 100 V. PCR products were purified using the AxyPrep™ Clean-Up Protocol (Axygen Scientific, Corning, NY, USA), following the manufacturer's guidelines.Purified triplicate PCR products were pooled and final concentrations were determined in duplicate using a Qubit 2.0 Fluorometer (T hermoFisher Scientific , Waltham, MA, USA).The amplicons were combined at equimolar concentrations prior to 2 × 250 bp sequencing on the MiSeq™ System (Illumina, San Diego, CA, USA) at the Natural History Museum, London, UK.Samples were demultiplexed based on the unique Golay barcodes per sample .T he raw sequences were submitted to GenBank SRA (BioProject ID: PR-JNA954357).
Amplicon sequence variant (ASV) sequence tables, taxonomic assignments, and sample metadata were combined in the phyloseq v1.38.0 pac ka ge (McMurdie and Holmes 2013 ).The 16S rRNA gene and 18S rRNA gene ASV tables wer e filter ed after taxonomic assignment.Initially, four samples were removed from the 18S

Sta tistical anal yses
Statistical analyses were conducted using the phyloseq v1.For all further statistical and taxonomic analyses, the ASV count data from the replicate samples from each water body were averaged.Several functions in the vegan v2.5.7 pac ka ge (Oksanen et al. 2020 ) were used for statistical analyses .T he ' cca ' function was used to produce canonical corr espondence anal ysis (CCA) plots to identify associations with measur ed envir onmental v ariables.Associations between sample composition and water temper atur e , pH, and conductivity, a verage air temperature, and geographic distance were assessed using the ' mantel ' function.Bray-Curtis dissimilarity matrixes were calculated on the av er a ged r elativ e-abundance tr ansformed data for each water body.Nonmetric multidimensional scaling (NMDS) of the 16S rRNA and 18S rRNA gene communities and significant differences in composition between sampling sites were assessed using the ' ANOSIM ' function with 999 permutations.

Functional annotation of 18S rRNA gene ASVs
Pr otist ASVs wer e assigned to tr ophic functional gr oups following taxonomic assignment.Protists were classified as autotr ophic phototr ophs and mixotr ophs, heter otr ophic bacteriv ores, eukaryv ores and omnivores , pathogens , or parasites .T he Cercozoa (Dumack et al. 2019 ), Chrysophyceae (Bock et al. 2022 ), Ciliophor a, and Dinofla gellata (Adl et al. 2019 ) were primarily assigned based on published taxonomic summaries for the respectiv e gr oups.Within PR2, Chrysophyceae ar e gr ouped into phylogenetic clades (Guillou et al. 2012 ).For this study, these clades were assigned a trophic function based on comparison to the taxonomic functional database by Bock et al. ( 2022 ).ASVs unassigned at the family level in clades B1, B2, and E were defined as mixotrophic-as all taxonomic lineages in these clades were assigned as such.Clades C, D, and F contain a mix of heter otr ophic and mixotr ophic linea ges and wer e ther efor e not assigned a function but can be assumed to hav e pha gotr ophic ca pability (Boc k et al. 2022 ).

Co-occurrence network analyses of 16S rRNA and 18S rRNA gene ASVs
Co-occurrence networks were constructed using the CoNet v1.1.1 plugin (Faust and Raes 2016 ) in Cytoscape v3.9.1 (Shannon et al. 2003 ).For the prokaryotic protist interaction network, metazoa and embryophyte-assigned ASVs wer e r emov ed fr om the 18S rRNA gene reads .T he 16S rRNA and 18S rRNA gene ASVs were r elativ e abundance tr ansformed, to corr ect for differ ential sequencing depth.To reduce false positives, ASVs were filtered to a minimum mean relative abundance of 1 × 10 −5 and a minimum pr e v alence of 25% (8/32 samples).For the eukaryotic protist interaction network, metazoa and embryophyte ASVs were retained, and samples wer e filter ed to the same abundance and pr e v alence thr esholds.Copr esence (positiv e) and m utual exclusion (negativ e) associations wer e inferr ed by fiv e separ ate methods: Spearman's r ank corr elation and K endall corr elation, c hosen as they do not assume linearity; mutual information (distance between probability distributions); Bray-Curtis; and Kullback-Leibler distance dissimilarity methods.To minimize sparsity effects, ASV rows with more than or equal to five null (0) values were removed ( row_minocc = 5).All filtered rows were summed into a single row that was k e pt for further pr ocessing.Samples wer e then standardized by conversion to column-wise proportional abundances ( col_norm ).The initial network was created using an automatic threshold of 1000 positive edges by all four measures.For each measure and edge, 100 permutations and 100 bootstr a p scor es wer e then generated, and the method-specific P -value scores were merged using Br own's method.False positiv es wer e detected and r emov ed fr om the final network by a ppl ying Benjamini-Hoc hber g corr ection.Unstable edges with a score outside the 95% confidence interval, as defined by the bootstr a p distribution, wer e discarded.Onl y edges supported by at least two methods and with P -values < .05were conserved in the final network.

Environmental conditions
Av er a ge air temper atur e and the number of days abov e fr eezing decreased with higher latitude ( Supplementary Table S1 1 ; Supplementary Table S2 ).On aver a ge, pH w as lo w est in the High Ar ctic ice shelf meltw ater ponds (6.14-6.98)and highest in ponds and lakes around Cambridge Bay (8.16-9.84).Water conductivity varied from 29.5 to 1365 μS cm −1 , with the lo w est av er a ge v alues in Umiujaq (29.5-112.5 μS cm −1 ) and highest in Cambridge Bay (300-1365 μS cm −1 ).

16S rRNA and 18S rRNA gene di v ersity of cyanobacterial mat communities across the Canadian Arctic
Across all c y anobacterial mat communities, 16S rRN A gene richness ( 1148) and e v enness (Shannon: 5.74, inv erse Simpson: 134.47)The mats from the lo w est latitude sampling sites in Kuujjuarpik contained the highest mean average prokaryotic richness (1494.75)and e v enness (Shannon = 6.22,inverse Simpson = 203.02)( Supplementary File 1 ), significantl y gr eater than that found in all higher latitude sampling sites by Wilcoxon signed-rank testing of ACE and Shannon diversity indices (Fig. 2 ; Supplementary File 1 ).The mats from the meltwater ponds of the High Arctic ice shelves had the lo w est av er a ge ric hness (389.33) and e v enness (Shannon = 4.41, inv erse Simpson = 43.56)and had significantly lo w er diversity than all lo w er latitude sampling sites by ACE and Shannon diversity indices (Fig. 2 ; Supplementary File 1 ).Eukary otic richness (ACE) w as significantly higher in the Kuujjuar a pik, Umiujaq, and Bylot Island sampling sites than all of the higher latitude sampling sites.Eukaryotic e v enness (Shannon and inverse Simpson) was significantly lo w er in the Ellesmere Island (Antoniades Pond and Ward Hunt Lake) mat communities, compared to all lo w er latitude sampling regions.

Abiotic dri v ers of cyanobacterial mat di v ersity
The reduction in 16S rRNA and 18S rRNA gene richness and e v enness in the c y anobacterial mat communities correlated with decr easing av er a ge annual temper atur es acr oss the latitudinal gr adient (Fig. 1 ).Furthermor e, ric hness and e v enness (Shannon) of the mat communities significantly positively correlated with w armer w ater temper atur es ( P < .001)( Supplementary Fig. S2 ).16S rRNA and 18S rRNA gene composition in cyanobacterial mats fr om Kujjuar a pik and Umiujaq sampling sites wer e most closel y affiliated to the water temper atur e v ector compar ed to all other sampling sites, by CCA (Fig. 3 A and B).Cyanobacterial mats from Cambridge Bay were correlated with water conductivity and pH vectors .T he mat communities from Resolute, Ellesmere Island, and the High Arctic ice shelves sho w ed little association with the measur ed envir onmental v ariables.

Taxonomic composition of cyanobacterial mats
A significant difference in prokaryotic ( R : 0.673, P < .0001)and eukaryotic ( R : 0.705, P < .0001)community composition was identified between sampling sites (Fig. 3 C and D).Ov er all c y anobacterial mat communities clustered by sampling sites, except for an ov erla p in the prokaryotic communities of Resolute and Ellesmere Island.The meltwater pond comm unities fr om the ice shelves were the most dissimilar from all other sampling regions.Eukaryotic comm unities fr om Kuujjuar a pik, Umiujaq, Cambridge Bay, and Bylot Island wer e mor e similar to each other than Resolute, Ellesmere Island, and the ice shelves (Fig. 3 D).

Assessment of trophic functional di v ersity of pr otists fr om 18S rRNA gene metabarcoding
Functional annotation was possible for 4263 out of 6296 of all protist ASVs (68%), the rest were left unassigned ( Supplementary File 2 ).Div erse phototr ophic, mixotr ophic, and heter otr ophic taxonomic gr oups wer e identified in all c y anobacterial mat communities.

Co-occurrence network analyses
The pr okaryotic pr otist inter action network contained 510 nodes (480 bacteria, 2 archaea, 24 protists, and 4 fungi) and 802 edges ( Supplementary Table S3 ).The eukaryotic protist interaction network contained 340 nodes (309 protists, 31 fungi, and 6 unassigned Opisthokonta) and 586 edges ( Supplementary Table S3 ).The structure of the tw o netw orks differed.The prokaryotic protist inter-action network consisted of three joined subnetworks, 23 major hubnodes (containing > 10 degrees), and several minor networks (21 nodes or fewer) (Fig. 6 A).The eukaryotic network consisted of se v er al smaller subnetworks and contained more negative interactions than the pr okaryotic pr otist inter action network (50 to 8 ) (Fig. 6 B).The eukaryotic network had a higher av er a ge number of neighbours (edge connections per node), a proxy for greater connectivity.The eukary otic netw ork had a higher proportion of edges pr oduced fr om thr ee to fiv e significant methods and a higher aver a ge number of methods per edge than the combined network (2.51 to 2.3) ( Supplementary Table S3 ).
Alpha pr oteobacteria, Planctomycetota, and Bacter oidota wer e the dominant prokaryotic orders in the prokaryotic protist interaction network.The major hubnodes were Hyphomonadaceae (Alpha pr oteobacteria), Lewinella (Bacter oidota), and Anaerolineae (Chlor oflexi spp.).Leptol yngb y aceae accounted for 17 out of 32 c y anobacteria nodes.Eukary otic groups w ere in lo w abundance ( ≤10 degrees) (Fig. 6 A).Heterotrophic Lobosa, Ciliophora, and Cercozoa contributed the most interactions in the eukaryotic protist interaction network, including Vampyrellida and Colpodea (Fig. 6 B).The major hubnodes were Navicula and Nitzschia spp.(Bacillariophyta).F igure 6. Co-occurrence netw ork analysis calculated on the ASVs across all mat samples .T he nodes r epr esent a unique ASV, and the size of the nodes is proportional to the connection degree .T he size of the edges are proportional to the number of methods that support the associated connection (two to five methods).The shape of the nodes indicates the domain: Bacteria (cir cles), Eukary ota (squares), and Archaea (diamonds).The barplots summarize the node degree distribution (number of connections) of each taxonomic group in the network.The green line indicates a positive connection and the pink a negative connection.(A) Prokaryotic protist interaction co-occurence network.(B) The eukaryotic protist interaction co-occurence network.

Arctic cyanobacterial mat di v ersity decreased across a latitudinal gradient
Across the Canadian Arctic, latitudinal gradients of decreasing temper atur e and light availability restrict biodiversity in the higher latitudes (Vincent 2010 ).The changes in terrestrial fauna and flor a ar e classified into Arctic ecozones, fr om the bor eal taiga, thr ough tundr a, to the polar desert (Wr ona et al. 2016 ).These empirical classifications are an example of the macroecological theory of the latitude diversity gradient (LDG); diversity decreases with proximity to the polar regions (Pianka 1966 ).Previous studies in the Canadian Arctic have identified LDGs in freshwater macr oinv ertebr ates (Lento et al. 2022 ) and marine microeukaryotes (Xu et al. 2022 ).To our knowledge, our study presents the first evidence of a LDG in c y anobacterial mats, microbial communities identified almost ubiquitously across freshwater systems in the Canadian Arctic (Jungblut et al. 2010, Vincent 2010 ).A significant negativ e r egr ession was identified betw een prokary otic and eukaryotic richness and evenness in c y anobacterial mats collected her e fr om 55 • N to 83 • N.
The reduction in prokaryotic and eukaryotic richness with increasing latitude may be due to increasingly restrictive environmental conditions for primary production in the High Arctic regions (Jungblut et al. 2017 ).The composition of the taiga region mat communities correlated with warmer air and water temperatures.In high-latitude regions, colder temperatures correspond with extended periods of ice cover, low light, and winter darkness, reducing annual primary production (Charvet et al. 2014 ).Across our sampling sites, the av er a ge number of months above freezing r anged fr om one to six, fr om the highest to lo w est latitude sampling regions .T he lo w er annual daylight and prolonged icecover limit the energy supply to phototrophs, reducing primary production and biomass growth in the High Arctic mat communities (Jungblut et al. 2017, Vincent et al. 2000 ).The 'species-energy hypothesis' of the LDG states that reduced solar energy at higher latitudes reduces primary productivity, thus limiting species richness (Currie et al. 2004 ).Colder temper atur es and fe wer days with light av ailability ar e likel y factors r estricting or ganic carbon accumulation within higher latitude microbial mat communities, resulting in reduced diversity.
Diversity of ecological communities is shaped by dispersal dynamics , en vironmental conditions , and biotic interactions (Leibold et al. 2004 ).Mat comm unity composition was consistentl y more similar within sampling sites than between, and the number of shared ASVs and community composition both increased with geogr a phical pr oximity.This is consistent with pr e vious biogeogr a phical studies of micr obial comm unities in the Canadian Ar ctic (Har ding et al. 2011, Jungblut et al. 2012, Comte et al. 2018 ).Prokaryotic composition and taxonomic diversity w ere, ho w ever, mor e consistent acr oss the LDG than eukaryotic communities within the c y anobacterial mats .T his suggests that particular bacterial phyla are essential for mat formation and structure (Jungblut et al. 2010 ).Compar ativ el y, eukaryotic ric hness and comm unity composition in the taiga and tundra ecozones were more distinct from the High Arctic polar desert and ice shelf mat communities .T he sparser structure of the eukary otic netw ork in comparison to the dense interactions in the prokaryotic community further supported gr eater heter ogeneity in eukaryotic diversity across the Arctic ecozones .T his is consistent with pr e vious clone libr ary surv eys of Arctic mat communities (Jungblut et al. 2012 ).Finally, a significant association between pH and eukaryotic composition identified by the Mantel test was not identified in the pr okaryotic comm unities .T he distinctions in eukaryotic community composition across gradients of changing climatic conditions suggests that microbial eukaryotic diversity may be more sensitiv e to envir onmental factors than pr okaryotic div ersity.In k ee ping with sensitivity to external conditions, distinct eukaryotic comm unities wer e identified between annual winter and summer conditions in Arctic lakes (Bock et al. 2014 ) and ponds (Simon et al. 2015, Potvin et al. 2022 ).
Due to logistical constraints, our analysis did not include nutrient conditions.In particular, nitrogen and phosphorus concentrations would influence microbial growth and taxonomic diversity within c y anobacterial mats in polar regions (Varin et al. 2010, Velázquez et al. 2017 ).While our study encompassed a variety of freshwater ecosystem types in the Canadian High Arctic, it is possible that the r elativ el y fe wer sampling sites at higher latitudes could have led to an under-representation of richness in Canadian High Arctic comm unities.Futur e work integrating nutrient measurements and spanning a broader range of sites across the Canadian High Arctic or extending into regions like Alaska or Greenland would enhance our findings and further test the latitudinal gradient hypothesis.

Cyanobacteria and heter otr ophic bacteria and nutrient cycling in Arctic cyanobacterial communities
Micr obial mats hav e been described as 'jungles of biodiv ersity' (Battin et al. 2016 ) and the organisms within them span the tree of life (Varin et al. 2010, Jungblut et al. 2012 ).Within all c y anobacterial mat communities, we identified a high diversity of bacteria, metazoa, fungi, and protists, as in previous studies in the Canadian Arctic (Jungblut et al. 2012, Mohit et al. 2017 ).Despite an ov er all r eduction in ric hness with latitude, all mat comm unities wer e consistentl y dominated by Pr oteobacteria, Cyanobacteria, Bacter oidota, Actinobacteriota, Verrucomicr obiota, Planctomycetota, and Chloroflexota, as reported in previous 16S rRNA gene surv eys of micr obial mats fr om the polar r egions (Kleinteic h et al. 2017, Greco et al. 2020, Jackson et al. 2021 ).
Within these microbial jungles, the k e ystone species are the c y anobacteria (Jungblut et al. 2010 ).Leptolyngbyaceae and Nostocaceae were the most abundant cyanobacterial families in our comm unities, consistent with pr e vious molecular and micr oscopy work on polar cyanobacterial mats (Vincent et al. 2000, Jungblut et al. 2010, Velázquez et al. 2017 ).Leptolyngb y aceae were also the most abundant c y anobacterial gr oup in the pr okaryotic pr otist inter action network, demonstr ating their significance in both primary production and three-dimensional organization of polar micr obial mat comm unities, pr oviding a substr ate for mor e specialized organisms (de los Ríos et al. 2004 ).The High Arctic mat communities had a higher proportion of Phormidiaceae , particularly Tychonema.Phormidium species may occur as a selective structural component to optimize carbon accumulation in low dissolved inorganic carbon en vironments , as discussed for Antarctic mat communities (Hawes et al. 2019 ).Tychonema spp.were identified as the most abundant c y anobacteria in pinnacle communities from Lake Untersee (Greco et al. 2020 ) and meltwater ponds in the Mc-Murdo Ice Shelf (Jackson et al. 2021 ), in k ee ping with the similarity between High Arctic ice shelf meltwater pond cyanobacterial mat communities and Antarctic microbial communities (Jungblut et al. 2017, Kleinteich et al. 2017 ).
Pr oteobacteria, primaril y fr om Alpha pr oteobacteria and Gamma pr oteobacteria, wer e the most abundant phyla in the mat comm unities, a consistent featur e of Arctic (Varin et al. 2010, Har ding et al. 2011), Antar ctic (Kleinteic h et al. 2017, Gr eco et al. 2020 ), and stream biofilms (Battin et al. 2016 ).Proteobacteria play an important role in decomposition and nutrient cycling in the mat comm unities.Se v er al Alpha pr oteobacteria orders degrade humic substances, a major component of dissolved organic matter in freshwater environments (Battin et al. 2016 ).Varin et al. ( 2010 ) pr e viousl y identified the high abundance of nitr ogen cycling-r elated genes originating fr om Pr oteobacteria.The significance of these heter otr ophic pr okary otes w as further highlighted in the network analyses, with Alphaproteobacteria, Planctomycetota, Bacter oidota, and Chlor oflexota forming the main hubnodes .T his suggests nutrient turno v er by heter otr ophic bacteria is essential to mat community function, especially in the subsurface layers (Battin et al. 2016, Velázquez et al. 2017 ).
Planctomycetes were the second most connected prokaryotic phylum in the combined network.The contribution of plancto-mycetes to Arctic mat communities has been less discussed than c y anobacteria and proteobacteria; ho w ever, they have been described in Antarctic lake comm unities (Gr eco et al. 2020 ) and are commonl y r eported in biofilm comm unities fr om extr eme oligotr ophic envir onments, wher e they degr ade algal biomass (Wiegand et al. 2018 ).Anaerobic planctomycete species are capable of anaerobic ammonium oxidation (anammox) and have been identified in aquatic biofilm communities (Lago and Bondoso 2014 ).Their contribution to the co-occurrence network suggests that planctomycetes may be key to degradation and nitrogen cycling in Arctic cyanobacterial mats.

Protists increase the trophic complexity of Arctic cyanobacterial mat communities
The functional diversity of protists identified in freshwater envir onments has c hanged our understanding of tr ophic inter actions in microbial food webs, where varied phototrophic and heter otr ophic gr oups may occupy se v er al tr ophic le v els (Arndt andNomdedeu 2016 , Burki et al. 2021 ).Our 18S rRNA gene surv ey identified phototr ophic and heter otr ophic bacterivor es, omniv ores, and eukaryv ores in all Arctic mat communities .T his is consistent with the notion that protists are common contributors to trophic interactions within the ubiquitous benthic c y anobacterial mat communities found in terrestrial aquatic systems across the polar regions (Vincent et al. 2000, Jungblut et al. 2012 ).Within the eukaryotic network, a diversity of interactions between phototr ophic, heter otr ophic, and par asitic gr oups was identified, supporting their contribution to trophic interactions and nutrient transfer within mat communities .Furthermore , the greater number of negative associations in the eukary otic netw ork suggests that specific niches may be occupied by multiple taxa between different mat communities.
We identified a pr oportionall y gr eater ric hness of phototr ophic organisms in the taiga and tundra mat communities and a proportionall y gr eater ric hness of bacterivor es and omnivor es in the High Arctic mat communities .T hese shifts in functional diversity may explain the distinction in eukaryotic composition of the c y anobacterial mats between these Arctic ecozones .T he greater div ersity of phototr ophic or ganisms in the lo w er latitude regions is likely a response to the extended summer period in the lo w er latitude en vironments .T his further highlights the influence of en vironmental conditions on eukaryotic diversity within the mat communities.
Phototrophic taxa had the highest relative abundance in the pr otist comm unities of the c y anobacterial mats, as identified in a pr e vious global study of fr eshwater pr otist div ersity (Singer et al. 2021 ).This is likely a reflection of the summer sampling period, during the months of maximum light availability.Phototrophic pr otists most likel y dw ell on the surface lay er of the mats, attenuating the penetration of light into deeper layers of the c y anobacterial mats, permitting growth of subsurface heterotrophic communities and dim-light-adapted c y anobacteria (Vincent et al. 1993, Battin et al. 2003 ).The most abundant phototrophs in our mat comm unities, the Chlor ophyta, r eac h maxim um gr owth during the early summer in Antarctic mat systems (Velázquez et al. 2017 ).It is possible that their high r elativ e abundance in our mat communities is a similar response to greater light availability.Mixotrophy is a common ada ptiv e str ategy in planktonic comm unities in High Arctic (Charvet et al. 2014 ) and per enniall y ice-cov er ed Antarctic lakes (Bielewicz et al. 2011 ); howe v er, mixotr ophy was not a common trophic strategy within our mat communities.Mixotr ophy is mor e ener geticall y costl y than heter otr ophy, and ther efor e may be less favourable in more nutrient-rich environments (Charvet et al. 2014 ).Mixotrophy w as, ho w ever, likely underestimated in our survey, with Dinoflagellata and Chlorophyta possibl y having mor e mixotr ophic r epr esentativ es (Adl et al. 2019, Pang et al. 2021 ).
Across the latitudinal gradient, Cercozoa, Ciliophora, and Lobosa were the most abundant heterotrophic protists identified in the mat communities and in the co-occurrence networks, consistent with a global metabarcoding survey of soil and freshwater environments (Singer et al. 2021 ).Cercozoa were mostly from the Filosa, which display gliding mobility; the microbial mats would provide a suitable substrate for such grazing heterotrophic activity (Bass et al. 2009 ).Vampyrellida , the most abundant eukaryvores in the mat communities, are specialized predators of filamentous algae and c y anobacteria, and are common to freshwaters, soils (Hess and Suthaus 2022 ), and polar cryoconites (Millar et al. 2021 ).Vampyrellida exhibit fast population growth in response to algal blooms (Hess and Suthaus 2022 ).Predatory Vampyr ellida may ther efor e act as r egulators of bloom cycles in the abundant phototrophic algae and c y anobacteria within the mat communities during the summer growth period.
Ciliophor a ar e common contributors to microbial mat communities (Dopheide et al. 2008, Battin et al. 2016 ).We identified a high abundance in all Arctic mat communities, comprising heter otr ophic bacterivor es, eukaryvor es, and par asites.Ciliates wer e pr e viousl y identified as heter otr ophic dominants in the winter community of a river ecosystem in southern Canada (Cruaud et al. 2019 ), and important members of the winter microbiome in a subarctic river (Blais et al. 2024 ).As such, they ma y pla y a k e y role in nutrient recycling in the Arctic mat communities during the winter months, in habitats that do not freeze to the bottom.Lobosa were the most abundant bacterivores in our mat communities and are known grazers of microbial mats (Tekle et al. 2022 ).
The most striking shift in pr otist div ersity acr oss the Arctic ecozones was the reduction in animal parasites in the High Arctic c y anobacterial mats, suggesting a significant biogeogr a phical barrier, most likely the restriction on host organisms, as identified within the metazoa in this study.Of the animal parasites identified, the most abundant were the Apicomplexa, diverse parasites of arthropods and crustacea (del Campo et al. 2019 ); the fish parasites, Hymenostomatia (Ciliophora) and Icthyosponida (Mesomycetozoa) (Adl et al. 2019 ); and the Harpellales, symbiotic fungi of insects (Wang et al. 2016 ).All of these groups were absent from the Markham and Ward Hunt ice shelves .T hese findings suggest that parasites could be used to gauge the northw ar d reductions of ecological barriers under climate change that are influenced by complex biotic and abiotic factors (Kutz et al. 2014 ).Ho w e v er, it is possible that certain phylogenetic groups were undetected due to PCR biases.Protists span an enormous diversity across the eukaryotic domain, making it difficult to design universal primers that cover all taxonomic groups (Burki et al. 2021 ).PCR-free shotgun sequencing or targeted PCR approaches are needed to convincingly test for the presence of animal parasitic protists in c y anobacterial mats in High Arctic freshwater en vironments .

Conclusions
Cyanobacterial mats are important for biomass and productivity in Arctic fr eshwater envir onments.This study sho w ed that pr okaryotic and micr obial eukaryotic species ric hness in fr eshwater microbial mats decreases along a latitudinal gradient from the subarctic to High Arctic based on 16S rRNA and 18S rRNA gene sequencing.Cyanobacteria and Proteobacteria were consistently the most abundant phototrophic and heterotrophic bacterial contributors to microbial mats, respectively.We identified a diversity of microbial eukaryotes comprising various physiologies and potentially contributing to many trophic interactions within abundant microbial mat communities across the Canadian Arctic, incr easing phototr ophic input during the summer months and facilitating nutrient turnover through diverse heterotrophic roles.Changes in eukaryotic diversity were distinct across latitudinal gr adients fr om the subarctic to High Arctic, including a notable increase in phototrophic microbial eukaryotes in lower latitude taiga and tundra communities and an increased relative abundance of heter otr ophic pr otists in High Arctic comm unities.Furthermor e, the r eduction in eukaryotic ric hness included a r eduction in metazoa and potential parasites of higher organisms in the High Arctic.The identified r esponsiv eness of protists to changing environmental conditions across these northern latitudes of Canada highlights their contribution to biodiversity, and their importance in understanding and monitoring biodiversity change in the Arctic.
38.0 (McMurdie and Holmes 2013 ) and vegan v2.5.7 (Oksanen et al. 2020 ) pac ka ges.ASV count data wer e not r ar efied prior to div ersity estimates to avoid inflation of false positives (McMurdie and Holmes 2014 ).Alpha-diversity measures were calculated for each sample individually.Changes in richness (ACE diversity index) and e v enness (Shannon and inverse Simpson diversity indices) with latitude were assessed by linear r egr ession.Differ ences in alpha diversity between sampling sites were tested by nonparametric Kruskal-Wallis and Wilcoxon tests.

Figure 1 .
Figure 1.Alpha-diversity estimates for each sample plotted by latitude (55-83 • N).Left column: pr okaryotic div ersity; right column: eukaryotic div ersity.(A, B) ACE diversity index, (C, D) Shannon diversity index, and (E, F) inverse Simpson diversity index.A linear model was used to create a trend line based on the diversity index values plotted against latitudinal coordinates.Shaded area around the line represents the 95% confidence level interval.

Figure 2 .
Figure 2. Alpha-diversity estimates for each sample grouped by sampling region, plotted left to right by latitude.Left column: prokaryotic diversity; right column: eukaryotic diversity.(A) and (B) = ACE diversity index, (C) and (D) = Shannon diversity index, and (E) and (F) = inverse Simpson diversity index.The boxplot r epr esents the interquartile range with the median denoted by the bold central line .T he whiskers represent 1.5 times the interquartile range and all outliers are denoted by a dot.Significant differences between sampling regions are denoted by an asterisk ( * P -value < .01,* * P -value < .001).

Figure 3 .
Figure3.Canonical-corr elation anal ysis of the (A) pr okary otic and (B) eukary otic communities in the mat samples plotted along with sample metadata significantly associated with the ASV distribution between water bodies as determined by permutational multivariate analysis of variance (PERMANOVA).Sample data mapped on graph, length, and direction of arrow demonstrate strength of association with the communities.Ordination of the r elativ e abundance count data of the (C) prokaryotic and (D) eukaryotic communites , a veraged for each water body, by two-dimensional Bray-Curtis NMDS.Significant differences in Bray-Curtis distance measures were identified between sampling regions by analysis of similarities (ANOSIM).

Figure 4 .
Figure 4. Taxonomic diversity of the microbial communities .T he size of the bubble is determined by the relative abundance of that taxon within the sample.Samples are plotted by latitude from lo w est to highest (55-83 • N). (A) Prokaryotic phyla and (B) eukaryotic divisions, low abundance phyla, here defined as < 1% of the total abundance for the prokaryotic community and 0.1% for the eukaryotic community, were grouped.The 15 most abundant families within (C) Proteobacteria and (D) Cyanobacteria.KJ = Kuujjuarapik, UM = Umiujaq, CB = Cambridge Bay, BY = Bylot Island, RE = Resolute, WH = Ward Hunt Lake, AP = Antoniades Pond, MKIS = Markham Ice Shelf, and WHIS = Ward Hunt Ice Shelf.

Figure 5 .
Figure 5. Relative abundance of ASVs assigned to each protist functional groups , a veraged by sample regions, ordered from left to right by increasing latitude.

Table 1 .
Sampling sites for mat communities and measured water conditions in the Canadian Arctic.

Sample ID Sampling region Water body Sampling period Coordinates ( • ) Temper a ture ( • C) pH Conductivity ( μS cm −1
(Jungblut et al. 2012 )ewer than five ASVs (CB8.3,CB1.2,BY2.2,and MKIS2).A raw sequence table of 38 631 unique ASVs was pr oduced fr om the 16S rRNA gene r eads.Pr e v alence filtering r emov ed all ASVs identified in a single sample from the 16S rRNA gene read sequence table , lea ving 19 481 unique ASVs .Furthermore , ASVs assigned to eukaryotic taxa were remov ed, along with an y mitoc hondria or c hlor oplast sequences, and sequences without phylum-le v el assignment, leaving 17 952 unique ASVs in the 16S rRNA gene sequence table.For the 18S rRNA gene , a ra w sequence table of 11 920 unique ASVs was produced from the reads.Prevalence filtering was not performed due to the expected lo w er abundance of eukaryotic micr oor ganisms in microbial mat communities(Jungblut et al. 2012 ).Taxonomic filtering r emov ed all non-eukaryotic reads and any sequences not assigned at the super gr oup le v el.The eukaryotic phyla Picozoa, Telonemia, and Str amenopiles_X wer e also r emov ed as they wer e extr emel y r ar e , ha ving onl y single ASVs pr esent in single samples.Phylogenetic distances were then used to a gglomer ate pr oximall y close ASVs using the ' tip_glom ' function in phyloseq ( H (Wright 2020 )enetic trees were produced from the filtered 16S rRNA and 18S rRNA gene ASVs using the DECIPHER v2.22.0 package(Wright 2020 ).Agglomeration produced a final ASV dataset of 15 250 unique ASVs from the 16S reads and 9354 unique ASVs from the 18S reads.